Research on Fuzzy Neural Network Based on Lyapunov Stability Theory and its Application

This paper proposes an adaptive fuzzy neural algorithm. In fact, this algorithm changes the parameters by using Lyapunov stability theory to ensure the stability. This algorithm didn´t need to seek the whole minimum value when it modifies the parameters. So the algorithm can reach the stability result more quickly than the conventional fuzzy neural algorithm. The analyses of theory prove the stability of the algorithm. Then we use this algorithm to control the activated sludge in wastewater treatment process, and compares with the conventional fuzzy neural algorithm. The results of simulations show the superiority of this algorithm and nicer robustness in the process. Besides, the structure of the new fuzzy neural network is simple and can be broadly used.